U.S. patent number 5,621,818 [Application Number 07/910,377] was granted by the patent office on 1997-04-15 for document recognition apparatus.
This patent grant is currently assigned to Fuji Xerox Co., Ltd.. Invention is credited to Kiyoshi Tashiro.
United States Patent |
5,621,818 |
Tashiro |
April 15, 1997 |
Document recognition apparatus
Abstract
A character recognition apparatus for recognizing characters in
a document by sequentially detecting one-character portions of
images in a document image and by recognizing the character images
of the one-character portions detected. The character recognition
apparatus includes a character detecting section for detecting an
image of one character from the document image; a character
recognizing section for recognizing the detected image of one
character and outputting a character code; and a control section
for effecting control such that the character image of one
character recognized by the character recognizing means is stored
in correspondence with the character code obtained as a result of
recognition, a comparison is made between the stored character
image and the image of a newly detected character, and the
character-code stored in correspondence with the relevant character
image is read as a result of recognition in a case where the
similarity of the images is sufficiently large. Character
recognition is effected in which a character image is detected from
the document image, the detected character image is recognized, and
the character code is outputted, thereby to sequentially recognize
a plurality of characters in the document.
Inventors: |
Tashiro; Kiyoshi (Kanagawa,
JP) |
Assignee: |
Fuji Xerox Co., Ltd. (Tokyo,
JP)
|
Family
ID: |
16335524 |
Appl.
No.: |
07/910,377 |
Filed: |
July 9, 1992 |
Foreign Application Priority Data
|
|
|
|
|
Jul 10, 1991 [JP] |
|
|
3-195100 |
|
Current U.S.
Class: |
382/227;
382/304 |
Current CPC
Class: |
G06K
9/685 (20130101) |
Current International
Class: |
G06K
9/68 (20060101); G06K 009/64 () |
Field of
Search: |
;382/34,1,25,27,14,37,38,40,30,218,209,227,226,229,170,203,304 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
Other References
Hagita et al, Handprinted Chinese Characters Recognition by
Peripheral Direction Contributivity Feature, Transactions of the
Institute of Electronics and Communication Engineers Oct. '83, vol.
J66-D, No. 10 pp. 1185-1192. .
Tadahiko Kumaamoto et al., On Speeding Candidate Selection In
Handprinted Chinese Character Recognition, Pattern Recognition,
vol. 24, No. 8, pp. 793-799..
|
Primary Examiner: Razavi; Michael T.
Assistant Examiner: Prikockis; Larry J.
Attorney, Agent or Firm: Finnegan, Henderson, Farabow,
Garrett & Dunner, L.L.P.
Claims
What is claimed is:
1. A document recognition apparatus in which character images are
detected from a document image to be recognized, and character
recognition for outputting a character code is effected so as to
sequentially recognize a plurality of different characters, said
document recognition apparatus comprising:
character detecting means for detecting character images;
character recognizing means for processing, when activated, each
detected character image to generate a corresponding character code
during a first time interval commencing from the activation to the
generation of the character code, said character recognizing means
includes means for outputting the generated corresponding character
code at the end of the first time interval;
character comparing means for comparing, when activated, each
detected character image with a stored character image during a
second time interval commencing from activation until the reading
of the character code corresponding to the stored character image,
said character comparing means includes means for reading the
character code corresponding to the stored character image in
response to a favorable character image comparison, and means for
outputting the read character code corresponding to the stored
character image at the completion of the second time interval;
and
control means for activating the character recognizing means and
the character comparing means at substantially the same time for
processing the same detected character image, said control means
including means for storing each recognized character image
together with its corresponding character code, and means
responsive to the outputting of a character code for deactivating
one of the character recognizing and character comparing means to
discontinue the corresponding process prior to the completion of
one of the first and second time intervals.
2. A document recognition apparatus as defined in claim 1 wherein
when said character recognizing means recognizes a character image
with a preset assurance, said storing means stores the recognized
character image together with the corresponding character code.
3. A document recognition apparatus as defined in claim 1 wherein
the character code corresponding to the stored character image is
read as a result of the favorable character image comparison when
the comparing means indicates that the similarity of the images
meets a predefined threshold, and the character code as a result of
recognition by said character recognizing means is outputted when
the comparing means indicates that the similarity of the images
does not meet a predefined threshold.
4. A document recognition apparatus as defined in claim 1 wherein
the storing means stores a character image and the corresponding
character code as a storage unit, the comparing means compares the
character image of each storage unit and the image of a newly
detected character, the reading means reads the character code
corresponding to the stored character image as a result of the
favorable character image comparison in the case where the
similarity of the images meets a predefined threshold, and the
storing means stores the recognized character image and the
corresponding character code where the similarity of the images
does not meet a predefined threshold.
5. A document recognition apparatus as defined in claim 4 wherein
frequency information for registering the frequency with which a
character code stored as a storage unit is read is stored with the
storage unit and at times when the storage means exceeds a maximum
capacity of storage, one storage unit is deleted from the storage
means on the basis of the frequency information.
6. A document recognition apparatus as defined in claim 1 wherein
the control means activates the character comparing means only at
times when there is at least one character image stored in
correspondence with a character code.
7. A document recognition apparatus as defined in claim 1 wherein
the character code is independent of the size of the image of the
character.
8. A document recognition apparatus in which kanji or kana
character images are detected from a document image to be
recognized, and character recognition for outputting a character
code is effected so as to sequentially recognize a plurality of
characters, said document recognition apparatus comprising:
character detecting means for detecting character images;
simple character image feature extracting means for extracting a
simple character image feature from the detected character
image;
character recognizing means for processing, when activated, each
detected character to generate a character code corresponding to
the extracted simple character image feature during a first time
interval commencing from the activation to the generation of the
character code, said character recognizing means includes means for
outputting a character code corresponding to the extracted simple
character image feature at the completion of the first time
interval;
character comparing means for comparing, when activated, the stored
simple character image feature with the extracted simple character
image feature during a second time interval commencing from
activation until the reading of the character code corresponding to
the stored simple character image feature, said character comparing
means including means for reading the character code corresponding
to the stored simple character image feature, and means for
outputting the character code corresponding to the stored simple
character image feature in response to a favorable comparison at
the end of the second time interval; and
control means for activating at substantially the same time for
processing of the same character image the character recognizing
means in response to each character image detected, and a character
comparing means in response to each extracted simple character
image feature from the character image, said control means
including means for storing each simple character image feature
together with its corresponding character code, and means
responsive to the outputting of a character code for deactivating
one of the character recognizing and character comparing means to
discontinue the corresponding process prior to the completion of
one of the first and second time intervals.
9. A document recognition apparatus as defined in claim 8 wherein
the control means activates the character comparing means only at
time when there is at least one simple character image feature
stored in correspondence with a character code.
10. A document recognition apparatus as defined in claim 8 wherein
the character code is independent of the size of the image of the
character.
11. A document recognition apparatus as defined in claim 8 wherein
when said character recognizing means recognizes a character image
with a preset assurance, said character image feature storing means
stores the simple character image feature of the recognized
character image together with the corresponding character code
obtained as a result of recognition of the recognized character
image.
12. A document recognition apparatus as defined in claim 8 wherein
the simple character image feature of a recognized character and
the corresponding character code are stored in said simple
character image feature storing means as a storage unit, a
comparison is sequentially made between the simple character image
feature stored as a storage unit and the simple character image
feature of a newly detected character, the reading means reads the
character code corresponding to the stored simple character image
feature as a result of the favorable character image comparison in
the case where the similarity of the simple character image
features meets a predefined threshold, the reading means reads the
character code recognized by said character recognizing means in a
case where the similarity of the simple character image features
does not meet a predefined threshold, and the storing means stores
the recognized simple character image feature and the corresponding
character code where the similarity of the images does not meet a
predefined threshold.
13. A document recognition apparatus as defined in claim 8 wherein
frequency information for registering the frequency with which a
character code stored is a storage unit is read is stored with the
storage unit, and if the storing means exceeds a maximum capacity
of storage, one storage unit is deleted from the storing means on
the basis of the frequency information.
Description
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a document recognition apparatus,
and more particularly to a character recognition apparatus for
recognizing characters in a document by sequentially detecting
one-character portions of images in a document image and by
recognizing the character images of the one-character portions
detected.
2. Description of the Related Art
Heretofore, document recognition apparatuses to which character
recognition devices have been developed as a method of inputting a
large volume of documents, ledgers, and the like which are written
by sentences in which kanji and kana are mixed. As shown in FIG. 9,
the document recognition apparatus comprises a character detecting
section 91 for detecting the character image of one character from
a document image, a character recognizing section 92 for
recognizing the detected character image of one character, and a
control section 93 for controlling the character detecting section
91 and the character recognizing section 92. The document
recognizing operation in the document recognition apparatus is
started as the control section 93 starts the character detecting
section 91 and the character recognizing section 92. When the
character detecting section 91 detects the character image of one
character and supplies the same to the character recognizing
section 92, the character recognizing section 92 effects feature
extraction processing and recognition processing with respect to
the character image of one character, and outputs a character code
as a result of recognition. This operation of recognizing one
character is repeatedly conducted, and each character in the
document image is recognized, thereby effecting document
recognition.
FIG. 10 is a block diagram illustrating an example of the
configuration of the character recognizing section. To recognize
the character images with high accuracy, it is necessary to clearly
express the differences between respective characters, and to
extract from the image to be recognized those features that are
unlikely to be affected by deformations, noise, and the like. For
this reason, various kinds of study have hitherto been made. For
instance, in a document "Hagita el al., Handprinted Chinese
Characters Recognition by Peripheral Direction Contributivity
Feature, Transactions of the Institute of Electronics and
Communication Engineers Oct. '83, Vol. J66-D, No. 10, pp 1185-1192"
a character recognizing system is reported which is capable of
effecting character discrimination with high accuracy with respect
to handwritten kanji through discrimination processing of a
two-stage system for conducting discrimination processing of
detailed portions with respect to narrowed-down candidate
characters after being classified on the basis of
rough-classification features.
In such a two-stage discrimination processing system, as shown in
the block diagram of FIG. 10, the configuration of the character
recognizing section for effecting character recognition processing
is comprised of an image feature normalizing section 101, a
rough-classification feature extracting section 102, a
rough-classification feature comparing section 103, a
rough-classification standard feature storing section 104, a
rough-classification sorting section 105, a precise-classification
feature extracting section 106, a precise-classification feature
comparing section 107, a precise classification standard feature
storing section 108, and a precise-classification sorting section
109, so as to effect character discrimination with high accuracy.
That is, first, when the image feature normalizing section 101
effects the normalization processing of the image to be recognized,
the rough-classification feature extracting section 102 extracts a
feature for rough classification. Then, by using the extracted
feature for rough classification, the rough-classification feature
comparing section 103 effects a comparison with a standard feature
stored in the rough-classification standard feature storing section
104. As a result of such a rough-classification comparison, the
rough-classification sorting section 105 effects a rough
classification. Then, the object of recognition is narrowed down,
and the precise-classification feature comparing section 107
performs a comparison with a standard feature stored in the
precise-classification standard feature storing section 108. As a
result of this comparison with the precise-classification feature,
the precise-classification sorting section 109 performs sorting
processing.
In addition, in general pattern recognition such as character
recognition, a method is also effective in which variations of the
objects of the respective features in a feature space are
statistically analyzed, and the variations are reflected on the
definition of the distance or the similarity. As an example of a
pattern recognition apparatus of this type, a pattern recognition
apparatus disclosed in Published Examined Japanese Patent
Application No. 19656/1981 has been proposed. In this pattern
recognition apparatus, the pattern recognition is effected on the
basis of the similarity between a standard pattern and an input
pattern. In the pattern recognition, M kinds of standard patterns
and N kinds of standard patterns perpendicular to the same are
prepared in advance as patterns corresponding to standard patterns
belonging to a specific class. Then, with respect to an arbitrarily
given input pattern, a determination is made of the difference
between, on the one hand, the sum of squares of the similarity of M
kinds produced between this input pattern and the M kinds of
standard patterns, and, on the other hand, similarly the sum of
squares of the similarity of N kinds produced with respect to the N
kinds of standard patterns. Then, processing is effected in which
whether or not the input pattern belongs to the relevant class is
determined by whether or not that value becomes a value greater
than a predetermined threshold value.
If an attempt is made to discriminate sentences in which kanji and
kana are mixed, or general graphic patterns with high accuracy,
very complicated recognition processing is required. In order to
improve the document recognition apparatus with respect to general
printed document, a multiplicity of features which are effective in
absorbing the difference between fonts are extracted, and
discrimination is effected by using a multiplicity of features. As
a result, although much time is required in the recognition
processing of one character, the character recognition can be
effected virtually reliably.
However, if complicated recognition processing is used to improve
the character recognition accuracy, the recognition speed declines,
and if, conversely, the processing is simplified to improve the
recognition speed, the recognition accuracy deteriorates. Thus,
there is the problem that the recognition speed and the recognition
accuracy are difficult to improve in a compatible manner.
SUMMARY OF THE INVENTION
The present invention has been devised to overcome the
above-described problems, and it is an object of the present
invention to provide a document recognition apparatus which
substantially improves the overall recognition speed during
recognition of a plurality of characters in a document image
without sacrificing the character recognition performance whereby
characters of various fonts can be recognized with high
accuracy.
To attain the aforementioned object, the document recognition
apparatus in accordance with the present invention is characterized
by being a document recognition apparatus in which a character
image is detected from a document image, the detected character
image is recognized, and character recognition for outputting a
character code is effected so as to sequentially recognize a
plurality of characters in the character image, the document
recognition apparatus comprising: character detecting means (11)
for detecting an image of one character from the document image;
character recognizing means (13) for recognizing the detected image
of one character and outputting a character code; and control means
(16) for effecting control such that the character image of one
character recognized by the character recognizing means is stored
in correspondence with the character code obtained as a result of
recognition, a comparison is made between the stored character
image and the image of a newly detected character, and the
character code stored in correspondence with the relevant character
image is read as a result of recognition in a case where the
similarity of the images is sufficiently large.
The document recognition apparatus is characterized by further
comprising: character image storing means (14) for storing the
character image of one character together with the character code
in correspondence with each other; and character image comparing
means (12) for determining the similarity between two one-character
portions of the character images, wherein the control means (16)
effects control such that the character image of one character
recognized by the character recognizing means (13) is stored in the
character image storing means (14) together with a corresponding
character code obtained as a result of recognition, a comparison is
made between the already stored character image and the image of a
newly detected character by means of the character image comparing
means (12), and the character code stored in correspondence with
the relevant character image is read as a result of recognition in
a case where the similarity of the images is sufficiently
large.
Here, the control means (16) is characterized in that only when the
assurance of a result of recognition by the character recognizing
means (13) is sufficiently large, the control means (16) stores in
the character image storing means (14) the relevant character image
together with the corresponding character code obtained as a result
of recognition.
In addition, the control means (16) is characterized by effecting
control such that the character image of one character and the
character code obtained as a result of recognition of the relevant
character image are stored as one storage unit (15) by being made
to corresponding to each other, a comparison is sequentially made
between the character image of each storage unit stored and the
image of a newly detected character, and the character code
corresponding to the stored character image is read as a result of
recognition in a case where the similarity of the images is
sufficiently large while the character code as a result of
recognition by the character recognizing means (13) is outputted in
a case where the similarity of the images is not sufficiently
large.
Furthermore, the control means (16) is characterized by effecting
control such that the character image of one character and the
character code obtained as a result of recognition of the relevant
character image are stored as one storage unit by being made to
corresponding to each other, a comparison is sequentially made
between the character image of each storage unit stored and the
image of a newly detected character, and the character code
corresponding to the stored character image is read as a result of
recognition in a case where the similarity of the images is
sufficiently large while the character code as a result of
recognition by the character recognizing means is outputted in a
case where the similarity of the images is not sufficiently large,
so as to store as a new storage unit the relevant character image
and the character code obtained as a result of recognition such
that the character image and the character code correspond to each
other.
In this case, frequency information for registering the frequency
with which the character code in a relevant storage unit is read is
additionally stored in the storage unit (15) for storing the
character image of one character together with the corresponding
character code obtained as a result of recognition of the relevant
character image, and in a case where the storage units exceed a
maximum capacity of storage, a storage unit to be detected is
determined on the basis of the frequency information on each of the
character images subjected to character recognition up until then,
and the storage unit including the character image and the
character code which are made to correspond to each other is stored
newly in the deleted storage unit.
In addition, the document recognition apparatus in accordance with
the present invention is characterized by being a document
recognition apparatus in which a character image is detected from a
document image, the detected character image is recognized, and
character recognition for outputting a character code is effected
so as to sequentially recognize a plurality of characters in the
character image, the document recognition apparatus comprising:
character detecting means (51) for detecting an image of one
character from the document image; character recognizing means (54)
for recognizing the detected image of one character and outputting
a character code; simple character image feature extracting means
(52) for extracting a simple character image feature from the
detected character image; character image feature storing means
(55) for storing the simple character image feature extracted from
the character image of one character and the character code which
are made to correspond to each other; simple character image
feature comparing means (53) for determining the similarity between
two one-character portions of the simple character image features;
and control means (57) for effecting control such that the
character code obtained as a result of recognition of the character
image recognized by the character recognizing means and the simple
character image feature of the relevant character image are stored
in the character image storing means by being made to correspond to
each other, a comparison is made between the simple character image
feature of the relevant character image with respect to the
character image of a newly detected character and the simple
character image feature stored in the character image feature
storing means, and the character code stored in correspondence with
the relevant simple character image feature is read as a result of
recognition in a case where the similarity of the simple character
image features as a result of comparison is sufficiently large.
In addition, in this document recognition apparatus, the control
means (57) is characterized in that only when the assurance of a
result of recognition by the character recognizing means is
sufficiently large, the control means (57) stores in the character
image feature storing means the simple character image feature of
the relevant character image together with the corresponding
character code obtained as a result of recognition of the relevant
character image.
Furthermore, in this document recognition apparatus, the control
means (57) is characterized in that the control means effects
control such that the simple character image feature of one
character and the character code obtained as a result of
recognition of the relevant character image are stored in the
character image feature storing means as one storage unit by being
made to corresponding to each other, a comparison is sequentially
made between the simple character image feature of each storage
unit stored and the simple character image feature of a newly
detected character, and the character code corresponding to the
stored simple character image feature is read as a result of
recognition in a case where the similarity of the simple character
image features is sufficiently large while the character code as a
result of recognition by the character recognizing means is
outputted in a case where the similarity of the simple character
image features is not sufficiently large, so as to store as a new
storage unit the relevant simple character image feature and the
character code obtained as a result of recognition such that the
simple character image feature and the character code correspond to
each other.
In this case, frequency information for registering the frequency
with which the character code in a relevant storage unit is read is
additionally stored in the storage unit (56) for storing the simple
character image feature of one character together with the
corresponding character code obtained as a result of recognition of
the relevant character image, and in a case where the storage units
exceed a maximum capacity of storage, a storage unit to be detected
is determined on the basis of the frequency information on each of
the character images subjected to character recognition up until
then, and the storage unit including the simple character image
feature and the character code which are made to correspond to each
other is stored newly in the deleted storage unit.
In the document recognition apparatus in accordance with the
present invention, the character detecting means (11) detects the
image of one character in a document image to be recognized, and
the character recognizing means (13) recognizes the detected image
of one character and outputs a character code. By means of the
control section (16), the character image of one character
recognized by the character recognizing means is stored by being
made to correspond to the character code obtained as a result of
recognition, and a comparison is made between the stored character
image and a newly detected image of one character. As a result of
this comparison, in a case where the similarity of the images is
substantially large, control is effected such that the character
code stored in correspondence with the relevant character image is
read as a result of recognition. As a result, through the simple
comparison of the similarity of the character images, the character
code of the result of character recognition is obtained without
particularly conducting the character recognition processing, with
accuracy similar to that in a case where recognition processing is
effected.
In addition, in the document recognition apparatus of the present
invention, the character detecting means (51) recognizes the
detected image of one character. At this time, the simple character
image feature extracting means (52) extracts a simple character
image feature from the character image detected by the character
detecting means (51). The simple character image feature comparing
means (53) effects a comparison of simple characters for
determining the similarity between two one-character portions of
the simple character image features. Stored in the character image
feature storing means (55) are the simple character image feature
extracted from the character image of one character and the
character code of the relevant character image by being made to
correspond to each other. The simple character image feature
comparing means (53) effects a comparison of similarity between the
simple character image feature stored in the character image
feature storing means (55) on the one hand, and the simple
character image feature extracted from the newly detected character
image of one character.
The control means (57) effects control such that the character code
obtained as a result of recognition of the character image
recognized by the character recognizing means and the simple
character image feature of the relevant character image are stored
in the character image storing means by being made to correspond to
each other, and a comparison is made between the simple character
image feature of the relevant character image with respect to the
character image of a newly detected character and the simple
character image feature stored in the character image feature
storing means. In addition, the control means (57) effects control
such that the character code stored in correspondence with the
relevant simple character image feature is read as a result of
recognition in a case where the similarity of the simple character
image features as a result of comparison is sufficiently large.
Through the above-described operation, the document recognition
apparatus effects the processing of document recognition in which a
character image is detected from a document image, the detected
character image is recognized, and the character recognition for
outputting a character code is effected, so as to sequentially
recognize the plurality of characters in the character image.
Namely, in the document recognition apparatus of this invention,
the following characteristic of a general printed document is
utilized. Use is made of the fact that the characters of the same
size and the same font are used frequently in individual documents,
and there are biases in the characters used in the individual
documents. As for the identical characters in a document, since the
characters of the same size and the same font are used frequently,
the character images themselves are similar. In order to determine
whether or not certain two character images are character images
representing an identical character, it is sufficient to conduct a
comparison of images using the character image itself, or a
comparison using a feature extracted very simply, without
conducting complicated feature extraction processing and
discrimination processing such as character recognition
processing.
Whether or a newly detected character image represents the same
character as the character image subjected earlier to complicated
recognition processing can be determined in a short period of time
by conducting a simple comparison of images or a comparison using a
feature extracted very simply. For this reason, if the character
image as it is after being subjected once to recognition
processing, or a feature extracted very simply from that character
image is stored in correspondence with the character code obtained
as a result of complicated recognition processing conducted
earlier, a determination is made as representing an identical
character when it can be judged through a simple comparison of
similarity that the newly detected character image is sufficiently
similar to the character image subjected earlier to recognition
processing. Thus, the character code which is the earlier result of
recognition can be used as the result of recognition of the newly
detected character image. In this case, since the character
recognition processing in which complicated feature extraction
processing and discrimination processing are conducted can be
omitted, so that it is possible to substantially reduce the
processing time from the time when the character image is detected
until the character code is obtained.
Consequently, the document recognition apparatus of this invention
is further provided with the character image storing means (14) for
storing the character image of one character together with the
character code in correspondence with each other; and the character
image comparing means (12) for determining the similarity between
two one-character portions of the character images, wherein the
control means (16) effects control such that the character image of
one character recognized by the character recognizing means (13) is
stored in the character image storing means (14) together with a
corresponding character code obtained as a result of recognition.
In addition, the control means (16) effects control such that a
comparison is made between the already stored character image and
the image of a newly detected character by means of the character
image comparing means (12), and the character code stored in
correspondence with the relevant character image is read as a
result of recognition in a case where the similarity of the images
is sufficiently large.
The characters used in individual documents have biases, and the
possibility of specific characters appearing repeatedly is high, so
that the proportion by which complicated recognition processing can
be omitted becomes very high as the above-described control of
recognition processing is performed.
For this reason, only when the assurance of a result of recognition
by the character recognizing means (13) is sufficiently large, the
control means (16) stores in the character image storing means (14)
the relevant character image together with the corresponding
character code obtained as a result of recognition. In addition,
the control means (16) effects control such that the character
image of one character and the character code obtained as a result
of recognition of the relevant character image are stored as one
storage unit (15) by being made to corresponding to each other, a
comparison is sequentially made between the character image of each
storage unit stored and the image of a newly detected character,
and the character code corresponding to the stored character image
is read as a result of recognition in a case where the similarity
of the images is sufficiently large while the character code as a
result of recognition by the character recognizing means (13) is
outputted in a case where the similarity of the images is not
sufficiently large.
Furthermore, the control means (16) effects control such that the
character image of one character and the character code obtained as
a result of recognition of the relevant character image are stored
as one storage unit by being made to corresponding to each other,
and when a comparison is sequentially made between the character
image of each storage unit stored and the image of a newly detected
character, the recognition processing is ended by reading the
character code corresponding to the stored character image as a
result of recognition in a case where the similarity of the images
is sufficiently large. It should be noted that if the similarity of
the images is not sufficiently large, the character code as a
result of recognition by the character recognizing means is
outputted, so as to store as a new storage unit the relevant
character image and the character code obtained as a result of
recognition such that the character image and the character code
correspond to each other. As a result, the new character images
subjected to complicated recognition processing are sequentially
stored by being made to correspond to the respective character
codes of the relevant character images obtained as a result of
recognition.
Furthermore, in a document to be recognized, in order to make use
of the fact that there are biases in the characters used in
individual documents, the character images or features extracted
simply from the respective character images are stored
preferentially with respect to characters whose frequency of
appearance is large. As a result, the frequency of omission of
recognition processing can be increased as practically as possible
with a small storage capacity, thereby improving the overall
recognizing speed.
For this reason, frequency information for registering the
frequency with which the character code in a relevant storage unit
is read is additionally stored in the storage unit (15) for storing
the character image of one character together with the
corresponding character code obtained as a result of recognition of
the relevant character image. Then, in a case where the storage
units exceed a maximum capacity of storage, a storage unit to be
detected is determined on the basis of the frequency information on
each of the character images subjected to character recognition up
until then, and the storage unit including the character image and
the character code which are made to correspond to each other is
stored newly in the deleted storage unit. As a result, although a
large storage capacity is required for storing character images,
even if the storing section has a limited storage capacity, it is
possible to sufficiently improve the recognizing speed.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are incorporated in and constitute
a part of the specification, illustrated presently preferred
embodiments of the invention and, together with the general
description given above and the detailed description of the
preferred embodiments given below, serve to explain the principles
of the invention. In the accompanying drawings:
FIG. 1 is a block diagram illustrating an overall configuration of
a document recognition apparatus in accordance with a first
embodiment of the present invention;
FIG. 2 is an explanatory diagram illustrating information in each
storage unit stored in a character image storing section;
FIG. 3 is a flowchart illustrating a processing flow of document
recognition processing controlled by a control section of the
document recognition apparatus;
FIG. 4 is a flowchart illustrating an example of storage control
processing in which in a case where a storage capacity exceeds a
maximum capacity, a storage unit to be deleted is selected and a
new storage unit is stored, by using frequency information added to
each storage unit of the character image storing section;
FIG. 5 is a block diagram illustrating an overall configuration of
a document recognition apparatus in accordance with a second
embodiment of the present invention;
FIGS. 6a and 6b are a diagram illustrating a mesh feature of a
simple character image feature;
FIG. 7 is an explanatory diagram illustrating information in each
storage unit stored in a character image feature storing
section;
FIG. 8 is a flowchart illustrating a processing flow of document
recognition processing controlled by the control section of the
document recognition apparatus in accordance with the second
embodiment;
FIG. 9 is a block diagram illustrating an overall configuration of
the document recognition apparatus; and
FIG. 10 is a block diagram illustrating a detailed configuration of
each portion of a character recognizing section.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
Referring to the drawings, a specific description will be given
hereafter of the embodiments of the present invention.
FIG. 1 is a block diagram illustrating an overall configuration of
a document recognition apparatus in accordance with the present
invention. FIG. 2 is an explanatory diagram illustrating
information in each storage unit stored in a character image
storing section. In FIGS. 1 and 2, reference numeral 11 denotes a
character detecting section; 12, a character image comparing
section; 13, a character recognizing section; 14, a character image
storing section; and 15, a storage unit for storing a character
image and a character code which are made to correspond to each
other. Frequency information is further stored in each storage unit
15 as additional information. In addition, numeral 16 denotes a
control section for controlling the overall document recognition
processing. Numeral 21 denotes character image information; 22,
character code information; and 23, frequency information.
A description will be given of the overall operation of the
document recognition apparatus thus arranged. If a document image,
i.e., an object to be recognized, is given, the character detecting
section 11 detects the image of one character from the document
image, and supplies the character image of one character detected
to the document image comparing section 12 and the character
recognizing section 13. When the character image of one character
is inputted, the character recognizing section 13 effects character
recognition processing with respect to the relevant character
image, including feature extraction processing,
rough-classification processing by means of features for rough
classification, and discrimination processing by means of detailed
features. The character recognition processing by this character
recognizing section 13 is processing in which complicated feature
extraction processing and the like are performed so as to effect
character recognition processing with high accuracy. Although this
character recognition processing requires much processing time,
when the character image of one character is given from the
character detecting section 11, processing is started, and the
processing of character recognition with high accuracy is
commenced.
Meanwhile, the already recognized character image is stored in the
character image storing section 14 as one storage unit 15 by being
made to correspond to a character code obtained as a result of
recognition thereof. The character images in the respective storage
units 15 which are stored in the character image storing section 14
are sequentially supplied to the character image comparing section
12, which performs a comparison between each of the character
images and each of the newly detected character images supplied
separately from the character detecting section 11, so as to
determine the similarity between the two character images. Since
the result of determination of comparison of the similarity by this
character image comparing section 12 is obtained sufficiently more
speedily than in the processing of the character recognition in the
character recognizing section 13, the control section 16 effects
control for reading a character code stored in the character image
storing section 14, in correspondence with the similarity obtained
as a result of determination of comparison of the similarity.
Alternatively, the control section 16 effects control for
outputting a character code from the character recognizing section
13 without performing reading.
That is, in a case where the similarity of the result of comparison
of the character images is sufficiently large, a relevant character
code is read from a storage unit stored in the character image
storing section 14 in correspondence with a corresponding character
image, and is outputted as a result of recognition. Then, an
instruction for stopping the processing is issued to the character
recognizing section 13 so as to end the character recognition
processing with respect to that character image. Subsequently, in
order to proceed to the recognition processing of an ensuing
character image, the control section 16 sends an instruction for
starting the processing of the ensuing character image to the
character detecting section 11, the character image comparing
section 12, and the character recognizing section 13.
Meanwhile, in a case where the similarity of the images obtained
from the character image comparing section 12 is not sufficiently
large, the control section 16 does not read a character code from
the storage unit in the character image storing section 14, and
waits until the recognition processing in the character recognizing
section 13 ends and a character code is obtained as a result of
recognition. The control section 16 then outputs the character code
outputted from the character recognizing section 13 as a result of
recognition. Upon completion of the processing by the character
recognizing section 13, in order to proceed to the recognition
processing of an ensuing character image, the control section 16
sends an instruction for starting the processing of the ensuing
character image to the character detecting section 11, the
character image comparing section 12, and the character recognizing
section 13.
In this case, before starting the processing of the ensuing
character image, the control section 16 effects control for storing
in the character image storing section 14 the character code
obtained from the character recognizing section 13, together with
the character image of a one-character portion of the relevant
character image, as a new storage unit 15 by causing that character
code obtained as a result of recognition to correspond to that
character image. Consequently, new character images subjected to
complicated recognition processing are sequentially made to
correspond to the relevant character codes of the character images,
respectively, and are stored in the character image storing section
14.
In the above-described manner, as shown in FIG. 2, the character
codes obtained by performing complicated recognition processing by
the character recognizing section 13 are each sequentially stored
in the character image storing section 14 as one storage unit 15,
together with the character image information 21 on one character
of the relevant character image such that the character code
information 22 obtained as a result of recognition is made to
correspond to that the character image information 21. In addition,
the character codes in parentheses in the character code
information 23 shown in FIG. 2 indicate that character codes of
next candidates outputted when character recognition processing was
performed are also stored as reference information. Moreover, the
character code information 22 stored by being made to correspond to
the character image information 21 stored in the storage unit 15
here may be stored in advance without particularly performing
character recognition processing with respect to the character
image of one character detected and by causing the character code
information 22 obtained as a result of correct recognition through
human judgment to correspond to that character image.
The frequency information 23 for registering the frequency with
which the character code information 22 in the relevant storage
unit 15 was read during document recognition processing is
additionally stored in the storage unit 15 which is stored in the
character image storing section 14, as shown in FIG. 2. For
instance, this frequency information 23 is set to a positive number
P when the image of one character and the character code are stored
newly in its storage unit. In addition, when the character image of
one character is detected from the document, and it is determined
that the character image of one character thus detected and the
character image of one character in that storage unit are
sufficiently similar, the frequency information is updated as a
positive number Q is added thereto. Furthermore, each time the
image of one character is detected from the document image, a
negative number R is added to the frequency information 23 in all
the storage units. Through these operations, the higher the
frequency of appearance of the image of one character up until then
and the more recent the appearance of the image of that character,
the greater the value of the frequency information.
In a document to be recognized, in a case where there are biases in
characters used in individual documents, the character image
storing section 14 can increase the frequency of omission of
character recognition processing with a small storage capacity, if
character images and character codes, with respect to characters
whose frequency of appearance shown in the frequency information is
high, are stored preferentially as storage units by being made to
correspond to each other, and if the image comparison is performed
preferentially by the character image comparing section 12.
Consequently, the overall processing speed in document recognition
processing improves.
The following control is effected as another method of using the
frequency information which is stored additionally in such
individual storage portions. That is, if there are numerous storage
units 15 already stored in the character image storing section 14,
and an attempt is made to store a storage unit of a new character
image, in the event that the maximum capacity of storage is to be
exceeded, storage units to be deleted are determined on the basis
of frequency information on the character images subjected to
character recognition up until then, and a storage unit in which
the character image and the character code are made to correspond
to each other is stored newly in the deleted storage unit. As a
result, in the documents to be recognized, by making use of the
bias characteristic in the characters used in the individual
documents, it is possible to increase as much as possible the
frequency of omission of recognition processing with a small
storage capacity, so that the overall recognition speed
improves.
FIG. 3 is a flowchart showing a processing flow of document
recognition processing-which is controlled by the control section
of the document recognition apparatus. Document recognition
processing will be described with reference to FIG. 3. In the
document recognition processing here, in Step 31, the image of one
character is first detected from the document image by controlling
the character detecting section 11. Then, in Step 32, the character
image comparing section 12 and the character image storing section
14 are controlled. Specifically, a comparison is made between the
character image read from the character image storing section 14
and the detected character image, and a determination is made as to
whether or not the image of one character sufficiently similar to
the image of one character detected is present in the character
image storing section. If a sufficiently similar image of one
character is present in the character image storing section, the
operation proceeds to processing in Step 33 to read and output the
character code stored in the character image storing section 14 by
being made to correspond to the relevant character image. Then, the
operation proceeds to Step 36 in which a determination is made as
to whether or not processing has been performed with respect to all
the characters in the document image. This determination as to
whether or not any unprocessed character image remains in the
character detecting section 41 is made by determining whether or
not an undetected character image area remains. If, in this
determination, it is determined that processing has not been
carried out with respect to all the characters in the document
image, the operation returns to Step 31, and the processing
starting with Step 31 is repeated.
Meanwhile, if it cannot be determined in Step 32 that the image of
one character sufficiently similar to the image of the character
detected is present in the character image storing section, the
operation proceeds to Step 34 in which the control section 16
controls the character recognizing section 13 to perform the image
recognition processing of the character image, and outputs the
character code outputted from the character recognizing section 13
as a result of recognition. Then, the operation proceeds to Step
35, in which case the control section 16 controls the character
image storing section 14 to store in the character image storing
section the character image of one character subjected to
recognition processing and the character code obtained as a result
of recognition thereof as one storage unit. Then, the operation
proceeds to Step 36 to effect the processing of Step 36, as
described above.
Such processing is repeatedly performed with respect to the
characters in the document image, and upon completion of processing
with respect to all the-characters in the document image, the
processing of the document image ends. In addition, in the
processing (Step 35) in which the control section 16 controls the
character image storing section 14 to store in the character image
storing section the character image of one character subjected to
recognition processing and the character code obtained as a result
of recognition thereof as one storage unit, if there are numerous
storage units 15 already stored in the character image storing
section 14, and an attempt is made to store a storage unit of a new
character image, in the event that the maximum storage capacity of
the character image storing section 14 is to be exceeded, storage
units having a low frequency of appearance are deleted on the basis
of the frequency information 23 on the character images stored
additionally in the storage unit 15, and storage control is
effected in which storage units of character images to be newly
stored are stored.
FIG. 4 is a flowchart showing an example of storage control
processing in which new storage units are stored by selecting the
storage units to be deleted in a case where the storage capacity
exceeds a maximum capacity, by using the frequency information
added to the respective storage units in the character image
storing section. Here, the number of storage units that can be
stored in the character image storing section is assumed to be N.
In this processing, as shown in FIG. 4, in Step 41, an index
variable i for designating each storage unit is first initialized
to 1. Then, by using this index variable i, a determination is made
in Step 42 as to whether or not the character image and the
character code are stored in the storage unit i. If the character
image and the character code are stored in the storage unit i, the
operation proceeds to Step 43 in which, in order to point an
ensuing storage unit, 1 is added to the index variable i, thereby
updating so as to designate the ensuing storage unit. In an ensuing
Step 44, a determination is made as to whether or not the index
variable i has exceeded a maximum value N. If the maximum value N
has not been exceeded, the operation returns to Step 42 to effect
processing again for determining whether or not the character image
and the character code have been stored in the storage unit i. This
processing is effected repeatedly, and if it is determined in Step
44 that the index variable i which has been sequentially updated
has exceeded the maximum value N, the storage units stored in the
character image storing section have reached the maximum capacity,
so that it is impossible to store a new storage unit including the
character image and the character code. For this reason, the
operation proceeds to Step 47 in which the previous character image
and character code which are stored in a storage unit j whose
frequency information is minimal are deleted, and a new character
image and a character code of that character image are stored in
this storage unit j. Then, in an ensuing Step 48, the frequency
information P is set in this storage unit j, and processing
ends.
Meanwhile, if it can be determined in the determination processing
in Step 42 that the character image and the character code are not
stored in the storage unit i, since this storage unit i is in a
vacant state, the character image and the character code which are
newly stored are stored in that storage unit i. For that reason,
the operation proceeds to Step 45 to store the character image and
the character code of that character image in the storage unit i.
Then, in an ensuing Step 46, the frequency information P is set in
this storage unit i, and processing ends.
When an attempt is made to newly store the image of one character
and the character code through the above-described storage
processing of the storage units, in a case where the image of one
character and the character code have already been stored in all of
the storage units, the previous character image and character code
stored in the storage unit whose frequency information is minimal
are deleted, and storage processing is effected in which a new
character image and a character code of that character image are
stored in this storage unit. Through this method of storing storage
units, the character image expressing a character whose frequency
of appearance is higher and which has appeared more recently
remains preferentially in the character image storing section 14.
In the document, since the character whose frequency of appearance
is higher and which has appeared more recently has a higher
probability of appearance, so that storage units each comprising a
character image and a character code of a high probability, which
can be used during the recognition of ensuing characters, can be
stored in the character image storing section.
Since the comparison of character images which is conducted in the
character image comparing section is sufficient if a rough
comparison of matching is performed between the character image
subjected earlier to character recognition and the character image
newly detected. Hence, even if a comparison is performed using a
very simple feature of the character image extracted from the
character image, the similarity can be determined sufficiently. For
instance, the comparison of the image features may be effected by
dividing the character image by a coarse mesh and by setting
average densities of mesh areas as a feature of the character
image. By so doing, the comparison processing of character image
features can be effected at high speed, thereby making it possible
to improve the processing speed of document recognition processing
as a whole. An embodiment of a document recognition apparatus using
such simple character image features will be described
hereafter.
FIG. 5 is a block diagram showing an overall configuration of a
document recognition apparatus in accordance with a second
embodiment of the present invention. FIG. 6 is a diagram
illustrating a mesh feature of a simple character image feature.
FIG. 7 is an explanatory diagram illustrating information in each
storage unit stored in a character image feature storing section.
In FIG. 5, reference numeral 51 denotes a character detecting
section; 52, a simple character image feature extracting section;
53, a character image comparing section; 54, a character
recognizing section; and 55, a character image feature storing
section. Numeral 56 denotes a storage unit for storing a simple
character image feature and a character code which are made to
correspond to each other, and frequency information is further
added to each storage unit 55 as additional information and is
stored therein. In addition, numeral 57 denotes a control section
for controlling the overall document recognition processing using
simple character image features.
A description will be given of the overall operation of the
document recognition apparatus thus arranged. If a document image,
i.e., an object to be recognized, is given, the character detecting
section 51 detects the image of one character from the document
image, and supplies the character image of one character detected
to the simple character image feature extracting section 52 and the
character recognizing section 54. When the character image of one
character is inputted, the character recognizing section 54 starts
character recognition processing with-respect to the relevant
character image, including feature extraction processing,
rough-classification processing by means of features for rough
classification, and discrimination processing by means of detailed
features. The character recognition processing by the character
recognizing section 54 is complicated processing such as ordinary
pattern recognition processing, and is processing which requires
much processing time. When the character image of one character is
given from the character detecting section 51, processing is
started, and the processing of character recognition with high
accuracy is commenced.
Meanwhile, when the character image of one character detected from
the character detecting section 51 is supplied thereto, the simple
character image feature extracting section 52 extracts a simple
character image feature of the mesh feature such as the one shown
in FIG. 6, and sends the same to the simple character image feature
comparing section 53. In addition, the simple character image
feature extracted from the already recognized character image and a
character code obtained as a result of recognition of that
character image are stored in the character image feature storing
section 55 as one storage unit 56 by being made to correspond to
each other, and frequency information being further added to and
stored in each storage unit 56. The simple character image features
in the respective storage units 56 which are stored in the
character image feature storing section 55 are sequentially
supplied to the simple character image feature comparing section
53, which performs a comparison between each of the simple
character image features and each of the newly detected simple
character image features supplied separately to the simple
character image feature comparing section 53 from the simple
character image feature extracting section 52. Then, the similarity
between the two simple character image features is determined by
the simple character image feature comparing section 53. Since the
result of determination of comparison of the similarity by this
simple character image feature comparing section 53 is obtained
sufficiently more speedily than in the processing of the character
recognition in the character recognizing section 54, the control
section 57 effects control for reading a character code stored in
the character image feature storing section 55, in correspondence
with the similarity obtained as a result of determination of
comparison of the similarity. Alternatively, the control section 57
effects control for outputting a character code from the character
recognizing section 54 without performing reading.
In a case where the similarity of the result of comparison of the
simple character image features is sufficiently large, a relevant
character code, which is stored by being made to correspond to the
relevant simple character image feature in the character image
feature storing section 45, is read and outputted as a result of
recognition. Then, in that case, an instruction for stopping the
processing is issued to the character recognizing section 54 so as
to end the character recognition processing with respect to that
character image. Subsequently, in order to proceed to the
recognition processing of the character image, the control section
57 sends an instruction for starting the processing of an ensuing
character image to the character detecting section 51, the simple
character image feature comparing section 53, and the character
recognizing section 54. In addition, the instruction for starting
the processing of the ensuing character image is also sent to the
character recognizing section 54.
Meanwhile, in a case where the similarity as a result of the
comparison of the simple character image features is not
sufficiently large, the control section 57 does not read a
character code from the storage unit 56 in the character image
feature storing section 55, and waits until the recognition
processing in the character recognizing section 54 ends and a
character code is obtained as a result of recognition. The control
section 57 then outputs the character code outputted from the
character recognizing section 54 as a result of recognition. Then,
upon completion of the processing by the character recognizing
section 54, in order to proceed to the recognition processing of an
ensuing character image, the control section 57 sends an
instruction for starting the processing of the ensuing character
image to the character detecting section 51, the simple character
image feature extracting section 52, the simple character image
feature comparing section 53, and the character recognizing section
54.
In this case, before starting the processing of the ensuing
character image, the control section 57 effects control for storing
in the character image feature storing section 55 the character
code obtained from the character recognizing section 54, together
with the simple character image feature extracted from that
character image, as a new storage unit 56 by causing that character
code obtained as a result of recognition to correspond to that
simple character image feature. Consequently, new character codes
of new character images obtained by effecting complicated
recognition processing with high accuracy over a long period of
time are sequentially made to correspond to the relevant simple
character image features, respectively, and are stored in the
character image feature storing section 14.
The simple character image feature used here is feature data in
which, as shown in FIG. 6(A), with respect to a character image 61
of one character, the character image is divided by a coarse mesh,
and the average image densities of the divided mesh area portions
are set as feature parameters. As a result, the simple character
image feature is set as a mesh feature 62 having 4.times.4 feature
parameters, as shown in FIG. 6(B). As for the simple character
image feature of such a mesh feature 62, simple character image
feature information 71 and character code information 72
corresponding thereto are stored in the character image feature
storing section 55 as one storage unit 56, as shown in FIG. 7. In
the same way as in the foregoing embodiment, further added to this
storage unit 56 is frequency information 73 for recording the
frequency with which the character code information 72 in that
storage unit 56 was read during the document recognition processing
through control by the control section 57.
In a document to be recognized, in a case where there are biases in
characters used in individual documents in the same way as in the
foregoing embodiment, the frequency information 73 stored here is
used to store the simple character image feature and the character
code as a storage unit by causing them to correspond to each other
preferentially with respect to the character whose frequency of
appearance is high. As a result, characters whose frequency of
appearance is high are preferentially subjected to the comparison
of similarity by the simple character image feature comparing
section 53. Thus, the character image feature storing section 55 is
capable of increasing the frequency of omission of character
recognition processing with a small storage capacity. In this case,
the overall processing speed in document recognition processing
also improves.
In addition, the following control is effected as another method of
using the frequency information 63 which is thus stored
additionally in the individual storage units 56. That is, if there
are numerous storage units 56 already stored in the character image
feature storing section 55 for storing the simple character image
features, and an attempt is made to store a new storage unit, in
the event that the maximum capacity of storage is to be exceeded,
storage units to be deleted are determined on the basis of
frequency information on the character images which appeared during
character recognition up conducted until then, and a storage unit
in which the character image and the character code are made to
correspond to each other is stored newly in the deleted storage
unit. As a result, in the documents to be recognized, it is
possible to make use of the bias characteristic in the characters
used in the individual documents, and it is possible to increase as
much as possible the frequency of omission of recognition
processing with a small storage capacity.
FIG. 8 is a flowchart showing a processing flow of document
recognition processing which is controlled by the control section
of the document recognition apparatus in accordance with the second
embodiment. Document recognition processing will be described with
reference to FIG. 8. In the document recognition processing here,
in Step 81, the image of one character is first detected from the
document image by controlling the character detecting section 51.
Then, in Step 82, the simple character image feature extracting
section 52 is controlled, and the simple character image feature is
extracted from the image of the detected character. Subsequently,
the operation proceeds to Step 83 to control the simple character
image feature comparing section 53 and the character image feature
storing section 55. Specifically, a comparison is made between the
simple character image feature read from the character image
feature storing section 55 and the simple character image feature
extracted from the detected character image, and a determination is
made as to whether or not a simple character image feature
sufficiently similar to the extracted simple character image
feature is present in the character image feature storing section.
If a sufficiently similar simple character image feature is present
in the character image feature storing section, the operation
proceeds to processing in Step 84 to read and output the character
code stored in the character image feature storing section 55 by
being made to correspond to the relevant simple character image
feature. Then, the operation proceeds to Step 87 in which a
determination is made as to whether or not processing has been
performed with respect to all the characters in the document image.
This determination as to whether or not any unprocessed character
image remains in the character detecting section 51 is made by
determining whether or not an undetected character image area
remains. If, in this determination, it is determined that
processing has not been carried out with respect to all the
characters in the document image, the operation returns to Step 81,
and the processing starting with Step 81 is repeated.
Meanwhile, if it cannot be determined in the determination
processing in Step 83 that a simple character image feature
sufficiently similar to the extracted simple character image
feature is present in the character image feature storing section,
the operation proceeds to Step 85 in which the control section 57
controls the character recognizing section 54 to perform the image
recognition processing of the character image, and outputs the
character code outputted from the character recognizing section 54
as a result of recognition. Then, the operation proceeds to Step
86, in which case the control section 57 controls the character
image feature storing section 55 to newly store in the character
image feature storing section the character code obtained as a
result of recognition of the character image of one character
subjected to recognition processing and the simple character image
feature extracted from that character image as one storage unit.
Then, the operation proceeds to Step 87, and in Step 87 which is
similar to the one described above, a determination is made as to
whether or not processing has been effected with respect to all the
characters in the document image. If it is determined that
processing has not been effected with respect to all the characters
in the document image, the operation returns to Step 81, and the
processing starting with Step 81 is repeated.
Such processing is repeatedly performed with respect to the
characters in the document image, and upon completion of processing
with respect to all the characters in the document image, the
processing of the document image ends. In the document image
recognition apparatus of this second embodiment, the simple
character image feature extracted from the character image is used
instead of the character image of one character in the first
embodiment. This simple character image feature is stored together
with a corresponding character code, and the comparison of the
simple character image features is conducted. Here, although a mesh
feature is used as the simple character image feature, another
feature may be used. Since this simple character image feature is
sufficient if the matching and comparison between the character
image of one character already processed and a newly detected
character image can be performed with high accuracy, so that an
arrangement may be provided such that square forms are extracted
from the character image, the number of the square forms is used as
the simple character image feature, and a comparison of the number
of the square forms is performed. Furthermore, still another
feature may be utilized.
Next, a description will be given of modifications of various
sections with respect to the embodiments of the present invention.
When an attempt is made to utilize the results of recognition of
the characters already processed, if a previous recognition result
is erroneous, that error will be repeated. To avoid this, an
arrangement is provided such that the assurance at the time when
the character image of one character is recognized is defined, and
only when it is greater than a predetermined threshold value, the
character image (or the simple character image feature) is stored
in the character image storing section (or the simple character
feature storing section).
As the definition of the assurance, the reciprocal of a distance
between the feature extracted from the inputted character image of
one character and the standard feature of a recognition candidate.
The fact that this assurance is sufficiently large means that the
feature extracted from the inputted image of one character and the
standard feature of the recognition candidate are sufficiently
close, and the probability of the recognized result being erroneous
becomes small. In addition, the similarity between features may be
used as another definition of assurance. As still another
definition of assurance, it is possible to use such as a ratio of a
distance to a second candidate to a distance to a first
candidate.
In addition, although, in the description of the foregoing
embodiments, a specific description has not been given of the
details of character recognition processing performed by the
character recognizing section since they are not related to an
essential portion of the present invention, it suffices if
character recognition processing with high recognition accuracy
which has hitherto been developed is used. In other words, any
recognition processing is applicable insofar as the recognition
processing makes it possible to input a character image and output
a character code as a result of recognition. In addition, this
character recognition processing need not necessarily be processing
for recognizing the character image of a one-character portion, and
may be processing for simultaneously recognizing a plurality of
characters. In this case, the character code which is outputted by
the character recognizing section and is stored in the character
image storing section or the simple character image feature storing
section may be a plurality of character codes with respect to the
character image of a one-character portion. The processing in which
the character image of the one-character portion is stored in
correspondence with a plurality of character codes and one
character code is selected from the plurality of character codes
may be effected by effecting discrimination by making use of the
grammatical nature of the language such as words and clauses on the
basis of the character codes of the context of the document being
consecutively subjected to character recognition. In addition, the
character codes may be internally defined codes in addition to the
ASCII codes, JIS codes, and the like.
In addition, the frequency information which is added to the
storage unit for storing the character image or the simple
character image feature is not limited to the one described above,
and may be based on another method of determination for expressing
a numerical value in which the subsequent probability of appearance
of each character is estimated from the previous state of
appearance of each character.
Furthermore, although in the foregoing embodiments a description
has been given of a case where characters to be subjected to
document recognition, in particular, are used as objects to be
recognized, the present invention is similarly applicable to
pattern recognition processing in which the same pattern appears a
plurality of times.
In the above, although a specific description has been given of the
present invention on the basis of a plurality of embodiments, the
present invention is not limited to these embodiments, and it goes
without saying that various modifications are possible within a
scope which does not depart from a gist thereof.
As described above, in accordance with the document recognition
apparatus of the present invention, the following control is
performed: The character image of one character recognized by the
character recognizing section is stored together with a
corresponding character code obtained as a result of recognition. A
comparison is made between the character image thus stored and the
image of a newly detected character. If the similarity of the
images is sufficiently large as a result of this comparison, the
character code stored in correspondence with that character image
is read as a result of recognition. For this reason, particularly
in a case where the character image which has already been
subjected to recognition processing appears again, the character
code is obtained at high speed only by the read processing of the
character code obtained as a result of recognition, through the
comparison of similarity of simple character images without
conducting complicated processing of character recognition. In this
case as well, the character code is obtained as a result of
character recognition with accuracy similar to the case where
ordinary recognition processing is carried out. Accordingly, the
document recognition apparatus is capable of improving the overall
recognition speed in the document recognition processing without
reducing the recognition accuracy.
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